Snapshot approach for underwriting valuation of asset portfolios

ABSTRACT

A method for valuing portfolio assets using a snapshot approach system is provided. The method includes segmenting portfolio assets into a predetermined number of segments based on financial attributes of each asset, selecting a representative sample of assets from each segment, valuing each asset in the representative asset sample, and calculating a value of the portfolio assets for bidding purposes based on the value of each asset in the representative asset sample.

BACKGROUND OF THE INVENTION

[0001] This invention relates generally to valuation methods forfinancial instruments, and more particularly to analyzing portfolios offinancial assets for the purpose of bidding to acquire those assets.

[0002] A large number of assets such as loans, e.g., thousands of loansor other financial instruments, sometimes become available for sale dueto economic conditions, the planned or unplanned divestiture of assetsor as the result of legal remedies. The sale of thousands of commercialassets or other financial instruments sometimes involving the equivalentof billions of dollars in assets must sometimes occur within a calendarmonth or less. Of course, the seller of assets wants to optimize thevalue of the portfolio, and will sometimes group the assets in“tranches.” The term “tranche” as used herein is not limited to foreignnotes but also includes assets and financial instrument groupingsregardless of country or jurisdiction.

[0003] Bidders may submit bids on all tranches, or on only sometranches. In order to win a tranche bid, a bidder typically must submitthe highest bid for that tranche. In connection with determining a bidamount to submit on a particular tranche, a bidder often will performdue diligence, including engaging underwriters to evaluate judiciouslyselected assets within a tranche and within the available limited time.In at least some known cases, the remainder of the assets within atranche are given an estimated underwritten value with the underwrittenassets used as a basis.

[0004] As a result of this process, a bidder may significantlyundervalue a tranche and submit a bid that is not competitive or bidhigher than the underwritten value and assume unquantified risk. Sincethe objective is to win each tranche at a price that enables a bidder toearn a return, losing a tranche due to significant undervaluation of thetranche represents a lost opportunity.

[0005] Currently, business enterprises assess an acquisition or sale ofassets and portfolios of assets on rapid schedules and often at greatdistances and varying time zones from the general management teams andfunctional heads which typically approve the offers for purchase or saleof these assets. Employees, partners and collaborators associated withdue diligence regarding the purchase of the assets are typically broughttogether for a relatively short duration of time to accomplish the duediligence. Typically due diligence activities are conducted in physicalproximity to the sources of information associated with the assets. Inat least some known cases, the collaborating personnel do not have thebenefit of training or knowledge of the complete set of analytical toolsat their disposal nor do they have “best practices” from previousefforts of a similar nature.

[0006] Consolidation of employees and collaborators into a remotephysical location for the duration of the due diligence effort is timeconsuming and expensive. In addition, persons on due diligence teamsrely on a small subset of other personnel who have detailed informationabout information sources, underwriting, analytical tools, reports, andcompleted analysis. The subset of individuals who have the informationbecome bottlenecks within a due diligence time line, driving up duediligence costs and adding time that could have otherwise been investedin more value added due diligence.

[0007] In summary, there are several factors that typically prevent asubstantive analysis on portfolios of financial assets. Some of thesefactors include incomplete information, limited time to bid date,alternative possible dispositions or resolutions of each asset, expenseassociated with gathering information, issues related to underwritingand legal, variation of expected assets resolution, uncertain futureexpenses related to collection on assets, large number of assets in aportfolio and model development for financial analysis.

BRIEF DESCRIPTION OF THE INVENTION

[0008] In one aspect, a method for valuing portfolio assets using asnapshot approach system is provided. The method includes segmentingportfolio assets into a predetermined number of segments based onfinancial attributes of each asset, selecting a representative sample ofassets from each segment, valuing each asset in the representative assetsample, and calculating a value of the portfolio assets for biddingpurposes based on the value of each asset in the representative assetsample.

[0009] In another aspect, a method for valuing portfolio assets using asnapshot approach system is provided. The method includes segmentingportfolio assets into a predetermined number of segments based onfinancial attributes of each asset, selecting a representative sample ofassets from each segment, performing an iterative and adaptive valuationin which each asset in the representative asset sample is individuallyvalued, and valuing the portfolio assets for bidding purposes when astopping criteria is satisfied by comparing the asset characteristics ofthe assets in the representative asset sample to the portfolio assetsand extrapolating the value of the portfolio assets from the value ofeach asset in the representative asset sample. The iterative andadaptive valuation includes underwriting each asset in therepresentative asset sample to generate underwriting data, valuing eachasset in the representative asset sample based on underwriting data,segmenting each asset in the representative asset sample based on assetcharacteristics such that each asset in the representative asset sampleis categorized with assets included in the representative asset samplehaving similar asset characteristics, and applying the stoppingcriteria.

[0010] In another aspect, a portfolio valuation system for snapshotvaluation of portfolio assets is provided. The system includes acentralized database for storing information relating to portfolioassets, a server system coupled to the database and configured toperform valuation process analytics, and at least one client systemconnected to the server system through a network. The server is furtherconfigured to segment portfolio assets into a predetermined number ofsegments based on financial attributes of each asset, select arepresentative sample of assets from each segment, value each asset inthe representative asset sample, and calculate a value of the portfolioassets for bidding purposes based on the value of each asset in therepresentative asset sample.

[0011] In another aspect, a portfolio valuation system for snapshotvaluation of portfolio assets is provided. The system includes acentralized database for storing information relating to portfolioassets, a server system coupled to the database and configured toperform valuation process analytics, and at least one client systemconnected to the server system through a network. The server is furtherconfigured to segment portfolio assets into a predetermined number ofsegments based on financial attributes of each asset, select arepresentative sample of assets from each segment, perform an iterativeand adaptive valuation in which each asset in the representative assetsample is individually valued, and value the portfolio assets forbidding purposes when a stopping criteria is satisfied by comparingasset characteristics of the assets in the representative asset sampleto the portfolio assets and extrapolating the value of the portfolioassets from the value of each asset in the representative asset sample.The iterative and adaptive valuation includes underwriting each asset inthe representative asset sample to generate underwriting data, valuingeach asset in the representative asset sample based on underwritingdata, segmenting each asset in the representative asset sample based onasset characteristics such that each asset in the representative assetsample is categorized with assets included in the representative assetsample having similar asset characteristics, and applying the stoppingcriteria.

[0012] In another aspect, a computer for snapshot valuation of portfolioassets is provided. The computer includes a database of portfolio assetsand is configured to enable valuation process analytics. The computer isprogrammed to segment portfolio assets into a predetermined number ofsegments based on financial attributes of each asset, select arepresentative sample of assets from each segment, value each asset inthe representative asset sample, and calculate a value of the portfolioassets for bidding purposes based on the value of each asset in therepresentative asset sample.

[0013] In another aspect, a computer for snapshot valuation of portfolioassets is provided. The computer includes a database of portfolio assetsand is configured to enable valuation process analytics. The computer isprogrammed to segment portfolio assets into a predetermined number ofsegments based on financial attributes of each asset, select arepresentative sample of assets from each segment, perform an iterativeand adaptive valuation in which each asset in the representative assetsample is individually valued, and value the portfolio assets forbidding purposes when a stopping criteria is satisfied by comparingasset characteristics of the assets in the representative asset sampleto the portfolio assets and extrapolating the value of the portfolioassets from the value of each asset in the representative asset sample.The iterative and adaptive valuation includes underwriting each asset inthe representative asset sample to generate underwriting data, valuingeach asset in the representative asset sample based on underwritingdata, segmenting each asset in the representative asset sample based onasset characteristics such that each asset in the representative assetsample is categorized with assets included in the representative assetsample having similar asset characteristics, and applying the stoppingcriteria.

[0014] In another aspect, a computer program embodied on a computerreadable medium for performing snapshot valuation of portfolio assets isprovided. The computer program includes computer code that segmentsportfolio assets into a predetermined number of segments based onfinancial attributes of each asset, selects a representative sample ofassets from each segment, values each asset in the representative assetsample, and calculates a value of the portfolio assets for biddingpurposes based on the value of each asset in the representative assetsample.

[0015] In another aspect, a computer program embodied on a computerreadable medium for performing snapshot valuation of portfolio assets isprovided. The computer program includes computer code that segmentsportfolio assets into a predetermined number of segments based onfinancial attributes of each asset, selects a representative sample ofassets from each segment, performs an iterative and adaptive valuationin which each asset in the representative asset sample is individuallyvalued, and values the portfolio assets for bidding purposes when astopping criteria is satisfied by comparing asset characteristics of theassets in the representative asset sample to the portfolio assets andextrapolating the value of the portfolio assets from the value of eachasset in the representative asset sample. The iterative and adaptivevaluation includes underwriting each asset in the representative assetsample to generate underwriting data, valuing each asset in therepresentative asset sample based on underwriting data, segmenting eachasset in the representative asset sample based on asset characteristicssuch that each asset in the representative asset sample is categorizedwith assets included in the representative asset sample having similarasset characteristics, and applying the stopping criteria.

BRIEF DESCRIPTION OF THE DRAWINGS

[0016]FIG. 1 is a flow diagram illustrating a known process for valuinga portfolio of assets.

[0017]FIG. 2 is a flow diagram illustrating segmenting and sampling aportfolio of assets in accordance with one embodiment of the presentinvention.

[0018]FIG. 3 is a flow diagram illustrating valuing a sampled portfolioof assets in accordance with one embodiment of the present invention;

[0019]FIG. 4 is a computer network schematic.

DETAILED DESCRIPTION OF THE INVENTION

[0020]FIG. 1 is a diagram 10 illustrating a known process for valuing alarge portfolio of assets 12 through an underwriting cycle and throughto making a bid for purchasing asset portfolio 12, for example, in anauction. FIG. 1 is a high level overview of a typical underwriting andextrapolation process 10 which is not iterative and not automated. Indiagram 10, underwriters underwrite 14 a number of individual assetsfrom portfolio 12 to generate an underwritten first portion 16 and anuntouched remainder portion 18. Before any of the assets areunderwritten, first portion 16 is zero percent and remainder portion 18is one hundred percent of portfolio 12. As the underwriting processprogresses, first portion 16 increases and remainder portion 18decreases. The objective is to underwrite as many assets as possiblebefore a bid is submitted for the purchase of asset portfolio. The teamof underwriters continues individually underwriting 14 until just beforea bid must be submitted. A gross extrapolation 20 is made to evaluateremainder portion 18. The extrapolated value 20 becomes thenon-underwritten inferred value 24. The gross extrapolation generates avaluation 24 for remainder portion 18. Valuation 22 is simply the totalof the individual asset values in first portion 16. However, valuation24 is a group valuation generated by extrapolation and may be discountedaccordingly. Valuations 22 and 24 are then totaled to produce theportfolio asset value 26. Valuation processes are performed on eachtranche of the portfolio.

[0021]FIG. 2 is a diagram illustrating one embodiment of a system 28 forasset segmenting and sampling 29 utilized in a snapshot approach forvaluing an asset portfolio. The term “snapshot approach” as used hereinrefers to the feature of the present invention that includes selecting arepresentative sample (i.e., a snapshot) of assets from a portfolio ofassets such that the representative sample can be valued and then usedto calculate the value of the assets within the asset portfolio.

[0022] Included in FIG. 2 are representations of process steps taken bysystem 28 in segmenting and sampling 29 asset portfolio 12 (shown inFIG. 1). System 28 is a phased approach that assigns certain basicfinancial attributes 30 to each asset within asset portfolio 12.Financial attributes 30 include, but are not limited to, amount ofunpaid principal balance (“UPB”) 32, collateral type 34, whether theloan is secured 36, whether the loan is unsecured 38, real estatesecurity 40, non-real estate security 42, litigation status 44, borroweroperational status 46, and payment behavior 48. Once each asset withinasset portfolio 12 is assigned financial attributes 30, a table 50 iscreated illustrating this information for each asset. An exemplaryembodiment of table 50 is shown below. Operational Status UPB_BinSecurity Profile Operating Non Operating A Real Estate Secured Non RealEstate Secured Unsecured B Real Estate Secured Non Real Estate SecuredUnsecured C Real Estate Secured Non Real Estate Secured Unsecured D RealEstate Secured Non Real Estate Secured Unsecured E Real Estate SecuredNon Real Estate Secured Unsecured

[0023] After each asset within asset portfolio 12 is assigned financialattributes 30 and table 50 is created, asset portfolio 12 undergoes asegmentation process 52 wherein each asset within asset portfolio 12 isplaced in a group or “segment” based on its assigned financialattributes 30. In other words, the assets within asset portfolio 12 thathave similarly assigned financial attributes 30 are grouped into aselected number of segments. Thus, each segment contains assets fromasset portfolio 12 that have similar financial attributes 30.

[0024] Following segmentation 52, a sampling 54 of the assets withinasset portfolio 12 is taken. Sampling 54 includes a representativesample of assets from each segment within asset portfolio 12. In theexemplary embodiment, sampling 54 is a stratified random sampling ofassets within asset portfolio 12 taken from each segment. Sampling 54includes a selected percentage of the assets within asset portfolio 12.For example, sampling 54 might include 25% by UPB of the assets includedwithin asset portfolio 12. Once sampling 54 is completed, the assetsselected by sampling 54 are placed in a “sampled” asset portfolio 56,which is a representative subset of asset portfolio 12. Sampled assetportfolio 56 then undergoes the underwriting process 58 as described ingreater detail below.

[0025] A technical effect produced by the system, which is described ingreater detail below, is that a business entity engaged in the businessof analyzing portfolios of financial assets for the purpose of biddingto acquire those assets may more quickly and more accurately generate abid to acquire those assets. The business entity achieves this technicaleffect by first analyzing and underwriting a representative sample ofthe assets within the portfolio, and then applying a statisticalanalysis to predict the values of the other assets within the portfolio.This process is iterated until an acceptable stopping criteria 60 issatisfied. When stopping criteria 60 is satisfied, asset portfolio 12can be valued 62.

[0026] In the example embodiment, stopping criteria 60 includes a knownstatistic employed in regression analysis that is referred to as an“R-Squared” calculation. “R-Squared” is a statistic employed inregression analysis that measures how much variance has been explainedby the regression model. It is a measure of how well the approximationmatches the actual data. More specifically, it is the proportion of thetotal variability (variance) in the dependent variable that can beexplained by the independent variables. R-Squared is also employed as ameasure of goodness of fit of the model. R-Squared ranges from 0% to100%. The greater the R-Squared, the better that approximation. If allthe observations fall on the regression line, R-Squared is equal to100%. An R-Squared of 25% means that 25% of variance in the dependentvariable can be accounted for by the independent variables you looked atin the multiple regression analysis. This means 75% of variance in thedependent variable is due to other causes. The variability in thedependent variable is partitioned into two component sums of squares:variability explained by the regression model and unexplained variation.To calculate R-Squared, the regression sums of squares is divided by thetotal sums of squares.

[0027] In the example embodiment, sampled asset portfolio 56, which is arepresentative subset of asset portfolio 12, is valued based on theunderwriting process. From the underwriting data collected on each assetincluded in sample asset portfolio 56, a valuation model is generated.The valuation model is then used to calculate the value of portfolio 12for bidding purposes. To determine whether stopping criteria 60 has beensatisfied, a user may utilize the valuation model to re-value sampleasset portfolio 56, and then compare the value of sample asset portfolio56 based on the underwriting data to the value of sample asset portfolio56 based on the valuation model to determine whether these values aresubstantially equal. If these values are substantially equal, thenstopping criteria 60 has been satisfied, and the iterative and adaptivevaluation process is complete and portfolio 12 can be valued for biddingpurposes.

[0028]FIG. 3 is a diagram illustrating one embodiment of a system 128utilizing a snapshot approach to valuing asset portfolio 12 (shown inFIG. 1). Included in FIG. 3 are representations of process steps takenby system 128 in valuing sampled asset portfolio 56 (shown in FIG. 2).The technical effect produced by system 128 is achieved by firstsegmenting and sampling 130 assets within an asset portfolio as shown inFIG. 2. Segmenting and sampling 130 is a phased approach that assignscertain basic financial attributes 30 (shown in FIG. 2) to each assetwithin the asset portfolio. Once each asset within the asset portfoliois assigned financial attributes 30, a table is created illustratingthis information for each asset. The asset portfolio then undergoes asegmentation process 52 (shown in FIG. 2) wherein each asset within theasset portfolio is placed in a group or “segment” based on its assignedfinancial attributes 30. Following segmentation 52, a sampling 54 (shownin FIG. 2) of the assets within the asset portfolio is taken. Sampling54 includes a representative sample of assets from each segment withinthe asset portfolio. Sampling 54 includes a selected percentage of theassets within the asset portfolio. Once sampling 54 is completed, theassets selected by sampling 54 are placed in a “sampled” asset portfolio56, which is a representative subset of the overall asset portfolio.

[0029] System 128 individually evaluates (“touches”) all assets insampled portfolio 56. After segmenting and sampling 130, system 128includes collecting 132 financial and other information relating to eachasset within sampled portfolio 56 so that each asset within sampledportfolio 56 may undergo an underwriting process 134. Prior tounderwriting process 134, underwriters may also perform valuations 136on collateral relating to at least one asset within sampled portfolio56. Collateral valuations 136 enable the underwriters to better evaluateassets within sampled portfolio 56. Additionally, the underwriters mayalso obtain and utilize external data 138 that relates to at least oneasset within sampled portfolio 56, for example, credit bureauinformation relating to a borrower is oftentimes used (e.g., Veritas;The D&B Corporation, and Credit Bureau Services).

[0030] During underwriting process 134, each asset within sampledportfolio 56 undergoes an iterative and adaptive valuation in which theassets in sampled portfolio 56 are individually valued, listedindividually in tables and then selected from the tables and groupedinto any desired or required groups or tranches for bidding purposes (asdescribed below.) As in diagram 10 (shown in FIG. 1), where underwritersbegin a full underwrite 14 (shown in FIG. 1) of individual assets inportfolio 12 (shown in FIG. 1) to produce a fully underwritten firstportion 16 (shown in FIG. 1) of assets, in system 128 underwriters begina full underwrite 134 of individual assets in sampled portfolio 56 toproduce a fully underwritten sampled portfolio 56. The informationgenerated through underwriting process 134, including the value of eachasset, is referred to as “underwriting data.”

[0031] After each asset within sampled portfolio 56 is valued throughunderwriting process 134, the underwriting data is stored in a masterdatabase 140. In one embodiment, database 140 is in communication with adatabase server (not shown in FIG. 3) and a server system (not shown inFIG. 3). Individual asset data for each asset in sampled portfolio 56 isentered into a database 140 from which selected data is retrieved basedon a given criteria for an iterative and adaptive process 142. Iterativeand adaptive process 142 includes grouping 144 the assets within sampledportfolio 56 based on like underwriting values and assetcharacteristics. Once grouping 144 is complete, iterative and adaptiveprocess 142 extrapolates 174 values for “like” assets or assets withsimilar characteristics so that a valuation model 176 (described below)may be generated for use in bidding 178. The values extrapolated mayinclude a nominal recovery percentage, and recovery strategy timing.

[0032] In one embodiment, database 140 is connected to a computer (notshown in FIG. 3) that is configured as a stand alone computer. Inanother embodiment, the computer is configured as a server connected toat least one client system through a network (shown and described inFIG. 4), such as a wide-area network (WAN) or a local-area network(LAN).

[0033] In one embodiment, once the groupings of assets is made, thenumber of samples to be taken and submitted for further underwritingreview is calculated by establishing the confidence level with whichstatements can be made about the total recoveries in each segment (k),establishing the precision with which one wishes to estimate the totalrecoveries in each segment (h) and providing an a priori estimate of thelevel and range of recoveries as a percentage of total Unpaid PrincipalBalance (UPB) (R), according to:${{Var}( {\hat{Y}}_{R} )} = {{n\lbrack {1 - \frac{n}{N}} \rbrack} \times \frac{\lbrack {\sum\limits_{1}^{N}\quad x_{i}} \rbrack^{2}}{\lbrack {\sum\limits_{1}^{n}\quad x_{i}} \rbrack^{2}} \times \frac{\sum\limits_{1}^{N}( \quad {y_{i} - {R\quad x_{i}}} )^{2}}{N - 1}}$

[0034] n=sample size

[0035] N=cluster size

[0036] x_(i)=UPB for sample i

[0037] y_(i)=recovery for sample i$R = {\frac{\sum\limits_{1}^{N}\quad y_{i}}{\sum\limits_{1}^{N}\quad x_{i}} = {{cluster}\quad {expected}\quad {recovery}\quad \%}}$

$\begin{matrix}{{h^{2} = {k^{2} \times {n\lbrack {1 - \frac{n}{N}} \rbrack} \times \frac{\lbrack {\sum\limits_{1}^{N}\quad x_{i}} \rbrack^{2}}{\lbrack {\sum\limits_{1}^{n}\quad x_{i}} \rbrack^{2}} \times \frac{\sum\limits_{1}^{N}( \quad {y_{i} - {R\quad x_{i}}} )^{2}}{N - 1}}}h = {{{error}\quad {tolerance}\quad {for}\quad {estimating}\quad Y} = {\sum\limits_{1}^{N}\quad {y_{i}\quad {with}\quad {\hat{Y}}_{R}}}}} & ( {{Equation}\quad A} ) \\{{{\hat{Y}}_{R} = {{\hat{R} \times {\sum\limits_{i = 1}^{N}\quad x_{i}}} = {{\frac{\sum\limits_{i = 1}^{n}\quad y_{i}}{\sum\limits_{i = 1}^{n}\quad x_{i}} \times {\sum\limits_{i = 1}^{N}\quad x_{i}}} = {\frac{\sum\limits_{i = 1}^{n}\quad {\rho_{i}x_{i}}}{\sum\limits_{i = 1}^{n}\quad x_{i}} \times {\sum\limits_{i = 1}^{N}\quad x_{i}}}}}}{k = {{constant}\quad {in}\quad {{Tchebyshev}'}s\quad {{Formula}:{{{{\hat{Y}}_{R} - \mu_{{\hat{Y}}_{R}}}} \leq {k\sqrt{{Var}( {\hat{Y}}_{R} )}\quad {with}\quad {probability}} \geq {1 - \frac{1}{k^{2}}}}}}}} & ( {{Equation}\quad B} )\end{matrix}$

[0038] By solving Equation A for n, the required sample size for thegiven cluster is obtained. Solving Equation B further allows the user tostate, with probability the calculated sample size, n, and associatedunderwritten values will estimate the total cluster recoveries to withinan error of h, assuming that estimates of total segment recoveries aredetermined using Equation B.

[0039] In practice, it is difficult to estimate variability in totalrecoveries without available data. A spreadsheet tool implements theabove by generating data in a Monte Carlo simulation, and guiding theuser through an analysis of the results until a favorable sample size isderived.

[0040] Table A provides an example output from a study of a group of 20loans, with estimated (expected) recoveries between 20% and 30% of UPB,and a range of UPB between 1MM and 2MM. Eight samples are needed toestimate the total recoveries for the 20 loans to within 10% of actual,with 75% confidence. TABLE A Sample Size Spreadsheet Wizard

[0041] The appropriate variance adjusted forecast is made for each assetand the valuation tables are constructed to include every asset in theportfolio. The recovery is valued with continuous probabilities at theunit of sale, which in one embodiment is a tranche. In the use of system28, internal rate of return (“IRR”) and variance would then be assessed.Preferred tranches have lower variances for a given IRR. The probabilityof each tranche's net present value (“NPV”) to be above 0 is assessedusing the project's discount rate. A discount rate is determined fromthe opportunity cost of capital, plus FX swap cost, plus risks ingeneral uncertainties inherent in the variances of forecasted cash flowrecovery.

[0042] “Underwriting” as used herein means a process in which a person(“underwriter”) reviews an asset in accordance with establishedprinciples and determines expected cash flows, subsequent to purchase,for the asset. During underwriting, the underwriter uses pre-existing orestablished criteria for the valuations. “Criteria” means rules relevantto asset value and a rating based on such categories. For example, as acriteria, an underwriter might determine three years of cash flowhistory of the borrower to be a category of information relevant toasset valuation and might give a certain rating to various levels ofcash flow.

[0043]FIG. 4 illustrates an exemplary system 400 in accordance with oneembodiment of the present invention. System 400 includes at least onecomputer configured as a server 402 and a plurality of other computers404 coupled to server 402 to form a network. In one embodiment,computers 404 are client systems including a web browser, and server 402is accessible to computers 404 via the Internet. In addition, server 402is a computer. Computers 404 are interconnected to the Internet throughmany interfaces including a network, such as a local area network (LAN)or a wide area network (WAN), dial-in-connections, cable modems andspecial high-speed ISDN lines. Computers 404 could be any device capableof interconnecting to the Internet including a web-based phone or otherweb-based connectable equipment, including wireless web and satellite.Server 402 includes a database server 406 connected to a centralizeddatabase 140 (also shown in FIG. 3) which contains data describing setsof asset portfolios. In one embodiment, centralized database 140 isstored on database server 406 and is accessed by users at one ofcomputers 404 by logging onto server sub-system 402 through one ofcomputers 404. In an alternative embodiment centralized database 140 isstored remotely from server 402. Server 402 is further configured toreceive and store information for the asset valuation methods describedabove.

[0044] While system 400 is described as a networked system, it iscontemplated that the methods and algorithms described herein forexamination and manipulation of asset portfolios are capable of beingimplemented in a stand-alone computer system that is not networked toother computers.

[0045] While the invention has been described in terms of variousspecific embodiments, those skilled in the art will recognize that theinvention can be practiced with modification within the spirit and scopeof the claims.

What is claimed is:
 1. A method for valuing portfolio assets using asnapshot approach system, said method comprising: segmenting portfolioassets into a predetermined number of segments based on financialattributes of each asset; selecting a representative sample of assetsfrom each segment; valuing each asset in the representative assetsample; and calculating a value of the portfolio assets for biddingpurposes based on the value of each asset in the representative assetsample.
 2. A method according to claim 1 wherein segmenting portfolioassets further comprises segmenting portfolio assets into apredetermined number of segments based on financial attributes of eachasset wherein the financial attributes of each asset include at leastone of an amount of unpaid principal balance (“UPB”), a collateral type,whether the loan is secured, whether the loan is unsecured, real estatesecurity, non-real estate security, a litigation status, a borroweroperational status, and payment behavior.
 3. A method according to claim1 wherein segmenting portfolio assets further comprises: assigningfinancial attributes to each asset in the portfolio wherein thefinancial attributes include at least one of an amount of unpaidprincipal balance (“UPB”), a collateral type, whether the loan issecured, whether the loan is unsecured, real estate security, non-realestate security, a litigation status, a borrower operational status, andpayment behavior; and categorizing each asset in the portfolio based onthe financial attributes assigned to each portfolio asset.
 4. A methodaccording to claim 1 wherein selecting a representative sample of assetsfrom each segment further comprises selecting a predetermined percentageof unpaid principal balance (“UPB”) of the portfolio assets.
 5. A methodaccording to claim 1 wherein valuing each asset in the representativeasset sample further comprises performing an iterative and adaptivevaluation in which each asset in the representative asset sample isindividually valued.
 6. A method according to claim 5 wherein performingthe iterative and adaptive valuation further comprises: underwritingeach asset in the representative asset sample to generate underwritingdata; valuing each asset in the representative asset sample based onunderwriting data; segmenting each asset in the representative assetsample based on asset characteristics such that each asset in therepresentative asset sample is categorized with assets included in therepresentative asset sample having similar asset characteristics;applying a stopping criteria; and valuing the portfolio assets forbidding purposes by comparing the asset characteristics of the assets inthe representative asset sample to the portfolio assets andextrapolating the value of the portfolio assets from the value of eachasset in the representative asset sample.
 7. A method according to claim6 further comprising storing the underwriting data in a centralizeddatabase.
 8. A method according to claim 6 wherein underwriting eachasset in the representative asset sample further comprises: collectingfinancial and business information relating to each asset in therepresentative asset sample; performing collateral valuations for atleast one asset in the representative asset sample; and utilizing creditbureau information for at least one asset in the representative assetsample.
 9. A method according to claim 6 wherein applying a stoppingcriteria further comprises performing an R-Squared analysis.
 10. Amethod according to claim 6 wherein applying a stopping criteria furthercomprises: valuing the representative asset sample based on underwritingdata; generating a valuation model for valuing the portfolio assets forbidding purposes by extrapolating the value of the portfolio assets fromthe value of the representative asset sample; utilizing the valuationmodel to re-value the representative asset sample; and determiningwhether the value of the representative asset sample based onunderwriting data and the value of the representative asset sample basedon the valuation model are substantially equal.
 11. A method accordingto claim 1 wherein calculating a value of the portfolio assets forbidding purposes further comprises: segmenting each asset in therepresentative asset sample based on asset characteristics such thateach asset in the representative asset sample is categorized with assetshaving similar asset characteristics; comparing the assetcharacteristics of the assets in the representative asset sample to theportfolio assets; extrapolating the value of the portfolio assets fromthe value of each asset in the representative asset sample; andcalculating a total value of the portfolio based on the extrapolation.12. A method according to claim 1 wherein calculating a value of theasset portfolio for bidding purposes further comprises generating avaluation model for use in bidding on the asset portfolio.
 13. A methodfor valuing portfolio assets using a snapshot approach system, saidmethod comprising: segmenting portfolio assets into a predeterminednumber of segments based on financial attributes of each asset;selecting a representative sample of assets from each segment;performing an iterative and adaptive valuation in which each asset inthe representative asset sample is individually valued, the iterativeand adaptive valuation includes underwriting each asset in therepresentative asset sample to generate underwriting data, valuing eachasset in the representative asset sample based on underwriting data,segmenting each asset in the representative asset sample based on assetcharacteristics such that each asset in the representative asset sampleis categorized with assets included in the representative asset samplehaving similar asset characteristics, and applying a stopping criteria;and valuing the portfolio assets for bidding purposes when the stoppingcriteria is satisfied by comparing the asset characteristics of theassets in the representative asset sample to the portfolio assets andextrapolating the value of the portfolio assets from the value of eachasset in the representative asset sample.
 14. A method according toclaim 13 further comprising: increasing the size of the representativesample of assets when the stopping criteria is not satisfied; performingan iterative and adaptive valuation in which each asset in the increasedrepresentative asset sample is individually valued, the iterative andadaptive valuation includes underwriting each asset in the increasedrepresentative asset sample to generate underwriting data, valuing eachasset in the increased representative asset sample based on underwritingdata, segmenting each asset in the increased representative asset samplebased on asset characteristics such that each asset in the increasedrepresentative asset sample is categorized with assets included in theincreased representative asset sample having similar assetcharacteristics, and applying a stopping criteria; and valuing theportfolio assets for bidding purposes when the stopping criteria issatisfied by comparing the asset characteristics of the assets in theincreased representative asset sample to the portfolio assets andextrapolating the value of the portfolio assets from the value of eachasset in the increased representative asset sample.
 15. A portfoliovaluation system for snapshot valuation of portfolio assets, said systemcomprising: a centralized database for storing information relating toportfolio assets; a server system coupled to said database andconfigured to perform valuation process analytics; and at least oneclient system connected to said server system through a network, saidserver further configured to: segment portfolio assets into apredetermined number of segments based on financial attributes of eachasset; select a representative sample of assets from each segment; valueeach asset in said representative asset sample; and calculate a value ofthe portfolio assets for bidding purposes based on the value of eachasset in said representative asset sample.
 16. A system according toclaim 15 wherein said server is further configured to segment portfolioassets into a predetermined number of segments based on financialattributes of each asset wherein said financial attributes of each assetinclude at least one of an amount of unpaid principal balance (“UPB”), acollateral type, whether the loan is secured, whether the loan isunsecured, real estate security, non-real estate security, a litigationstatus, a borrower operational status, and payment behavior.
 17. Asystem according to claim 15 wherein said server is further configuredto: assign financial attributes to each asset in said portfolio whereinsaid financial attributes include at least one of an amount of unpaidprincipal balance (“UPB”), a collateral type, whether the loan issecured, whether the loan is unsecured, real estate security, non-realestate security, a litigation status, a borrower operational status, andpayment behavior; and categorize each asset in said portfolio based onsaid financial attributes assigned to each portfolio asset.
 18. A systemaccording to claim 15 wherein said server is further configured toselect a representative sample of assets from each segment based on apredetermined percentage of unpaid principal balance (“UPB”) of saidportfolio assets.
 19. A system according to claim 15 wherein said serveris further configured to perform an iterative and adaptive valuation inwhich each asset in said representative asset sample is individuallyvalued.
 20. A system according to claim 19 wherein said server isfurther configured to perform said iterative and adaptive valuation by:underwriting each asset in said representative asset sample to generateunderwriting data; valuing each asset in said representative assetsample based on underwriting data; segmenting each asset in saidrepresentative asset sample based on asset characteristics such thateach asset in said representative asset sample is categorized withassets in said representative asset sample having similar assetcharacteristics; applying a stopping criteria; and valuing saidportfolio assets for bidding purposes by comparing said assetcharacteristics of said assets in said representative asset sample tosaid portfolio assets and extrapolating the value of said portfolioassets from the value of each asset in said representative asset sample.21. A system according to claim 20 wherein said server is furtherconfigured to store said underwriting data in said centralized database.22. A system according to claim 20 wherein said server is furtherconfigured to underwrite each asset in said representative asset sampleby: collecting financial and business information relating to each assetin said representative asset sample; performing collateral valuationsfor at least one asset in said representative asset sample; andutilizing credit bureau information for at least one asset in saidrepresentative asset sample.
 23. A system according to claim 20 whereinsaid server is further configured to apply a stopping criteria byperforming an R-Squared analysis.
 24. A system according to claim 20wherein said server is further configured to apply a stopping criteriaby: valuing said representative asset sample based on said underwritingdata; generating a valuation model for valuing said portfolio assets forbidding purposes by extrapolating the value of said portfolio assetsfrom the value of said representative asset sample; utilizing saidvaluation model to re-value said representative asset sample; anddetermining whether the value of said representative asset sample basedon said underwriting data and the value of said representative assetsample based on said valuation model are substantially equal.
 25. Asystem according to claim 15 wherein said server is further configuredto calculate a value of said portfolio assets for bidding purposes by:segmenting each asset in said representative asset sample based on assetcharacteristics such that each asset in said representative asset sampleis categorized with assets having similar asset characteristics;comparing the asset characteristics of the assets in said representativeasset sample to said portfolio assets; extrapolating the value of saidportfolio assets from the value of each asset in said representativeasset sample; and calculating a total value of said portfolio based onsaid extrapolation.
 26. A system according to claim 15 wherein saidserver is further configured to generate a valuation model for use inbidding on said asset portfolio.
 27. A portfolio valuation system forsnapshot valuation of portfolio assets, said system comprising: acentralized database for storing information relating to portfolioassets; a server system coupled to said database and configured toperform valuation process analytics; and at least one client systemconnected to said server system through a network, said server furtherconfigured to: segment portfolio assets into a predetermined number ofsegments based on financial attributes of each asset; select arepresentative sample of assets from each segment; perform an iterativeand adaptive valuation in which each asset in said representative assetsample is individually valued, said iterative and adaptive valuationcomprises underwriting each asset in said representative asset sample togenerate underwriting data, valuing each asset in said representativeasset sample based on underwriting data, segmenting each asset in saidrepresentative asset sample based on asset characteristics such thateach asset in said representative asset sample is categorized withassets included in said representative asset sample having similar assetcharacteristics, and applying a stopping criteria; and value saidportfolio assets for bidding purposes when said stopping criteria issatisfied by comparing asset characteristics of the assets in saidrepresentative asset sample to said portfolio assets and extrapolatingthe value of said portfolio assets from the value of each asset in saidrepresentative asset sample.
 28. A system according to claim 27 whereinsaid server is further configured: increase the size of therepresentative sample of assets when said stopping criteria is notsatisfied; perform an iterative and adaptive valuation in which eachasset in said increased representative asset sample is individuallyvalued, said iterative and adaptive valuation includes underwriting eachasset in said increased representative asset sample to generateunderwriting data, valuing each asset in said increased representativeasset sample based on underwriting data, segmenting each asset in saidincreased representative asset sample based on asset characteristicssuch that each asset in said increased representative asset sample iscategorized with assets included in said increased representative assetsample having similar asset characteristics, and applying said stoppingcriteria; and value said portfolio assets for bidding purposes when saidstopping criteria is satisfied by comparing asset characteristics of theassets in said increased representative asset sample to said portfolioassets and extrapolating the value of said portfolio assets from thevalue of each asset in said increased representative asset sample.
 29. Acomputer for snapshot valuation of portfolio assets, said computerincluding a database of portfolio assets and configured to enablevaluation process analytics, said computer programmed to: segmentportfolio assets into a predetermined number of segments based onfinancial attributes of each asset; select a representative sample ofassets from each segment; value each asset in said representative assetsample; and calculate a value of the portfolio assets for biddingpurposes based on the value of each asset in said representative assetsample.
 30. A computer according to claim 29 programmed to segmentportfolio assets into a predetermined number of segments based onfinancial attributes of each asset wherein said financial attributes ofeach asset include at least one of an amount of unpaid principal balance(“UPB”), a collateral type, whether the loan is secured, whether theloan is unsecured, real estate security, non-real estate security, alitigation status, a borrower operational status, and payment behavior.31. A computer according to claim 29 programmed to segment portfolioassets by: assigning financial attributes to each asset in saidportfolio wherein said financial attributes include at least one of anamount of unpaid principal balance (“UPB”), a collateral type, whetherthe loan is secured, whether the loan is unsecured, real estatesecurity, non-real estate security, a litigation status, a borroweroperational status, and payment behavior; and categorizing each asset insaid portfolio based on said financial attributes assigned to eachportfolio asset.
 32. A computer according to claim 29 programmed toselect a representative sample of assets from each segment based on apredetermined percentage of unpaid principal balance (“UPB”) of saidportfolio assets.
 33. A computer according to claim 29 programmed toperform an iterative and adaptive valuation in which each asset in saidrepresentative asset sample is individually valued.
 34. A computeraccording to claim 33 programmed to perform said iterative and adaptivevaluation by: underwriting each asset in said representative assetsample to generate underwriting data; valuing each asset in saidrepresentative asset sample based on underwriting data; segmenting eachasset in said representative asset sample based on asset characteristicssuch that each asset in said representative asset sample is categorizedwith assets having similar asset characteristics; applying a stoppingcriteria; and valuing said portfolio assets for bidding purposes bycomparing said asset characteristics of said assets in saidrepresentative asset sample to said portfolio assets and extrapolatingthe value of said portfolio assets from the value of each asset in saidrepresentative asset sample.
 35. A computer according to claim 34programmed to store said underwriting data in a centralized database.36. A computer according to claim 34 programmed to underwrite each assetin said representative asset sample by: collecting financial andbusiness information relating to each asset in said representative assetsample; performing collateral valuations for at least one asset in saidrepresentative asset sample; and utilizing credit bureau information forat least one asset in said representative asset sample.
 37. A computeraccording to claim 34 programmed to apply a stopping criteria byperforming an R-Squared analysis.
 38. A computer according to claim 34programmed to apply a stopping criteria by: valuing said representativeasset sample based on said underwriting data; generating a valuationmodel for valuing said portfolio assets for bidding purposes byextrapolating the value of said portfolio assets from the value of saidrepresentative asset sample; utilizing said valuation model to re-valuesaid representative asset sample; and determining whether the value ofsaid representative asset sample based on said underwriting data and thevalue of said representative asset sample based on said valuation modelare substantially equal.
 39. A computer according to claim 29 programmedto calculate a value of said portfolio assets for bidding purposes by:segmenting each asset in said representative asset sample based on assetcharacteristics such that each asset in said representative asset sampleis categorized with assets having similar asset characteristics;comparing the asset characteristics of the assets in said representativeasset sample to said portfolio assets; extrapolating the value of saidportfolio assets from the value of each asset in said representativeasset sample; and calculating a total value of said portfolio based onsaid extrapolation.
 40. A computer according to claim 29 programmed togenerate a valuation model for use in bidding on said asset portfolio.41. A computer for snapshot valuation of portfolio assets, said computerincluding a database of portfolio assets and configured to enablevaluation process analytics, said computer programmed to: segmentportfolio assets into a predetermined number of segments based onfinancial attributes of each asset; select a representative sample ofassets from each segment; perform an iterative and adaptive valuation inwhich each asset in said representative asset sample is individuallyvalued, said iterative and adaptive valuation comprises underwritingeach asset in said representative asset sample to generate underwritingdata, valuing each asset in said representative asset sample based onunderwriting data, segmenting each asset in said representative assetsample based on asset characteristics such that each asset in saidrepresentative asset sample is categorized with assets included in saidrepresentative asset sample having similar asset characteristics, andapplying a stopping criteria; and value said portfolio assets forbidding purposes when said stopping criteria is satisfied by comparingasset characteristics of the assets in said representative asset sampleto said portfolio assets and extrapolating the value of said portfolioassets from the value of each asset in said representative asset sample.42. A computer according to claim 41 programmed to: increase the size ofthe representative sample of assets when said stopping criteria is notsatisfied; perform an iterative and adaptive valuation in which eachasset in said increased representative asset sample is individuallyvalued, said iterative and adaptive valuation includes underwriting eachasset in said increased representative asset sample to generateunderwriting data, valuing each asset in said increased representativeasset sample based on underwriting data, segmenting each asset in saidincreased representative asset sample based on asset characteristicssuch that each asset in said increased representative asset sample iscategorized with assets included in said increased representative assetsample having similar asset characteristics, and applying said stoppingcriteria; and value said portfolio assets for bidding purposes when saidstopping criteria is satisfied by comparing asset characteristics of theassets in said increased representative asset sample to said portfolioassets and extrapolating the value of said portfolio assets from thevalue of each asset in said increased representative asset sample.
 43. Acomputer program embodied on a computer readable medium for performingsnapshot valuation of portfolio assets, said computer program comprisingcomputer code that: segments portfolio assets into a predeterminednumber of segments based on financial attributes of each asset; selectsa representative sample of assets from each segment; values each assetin said representative asset sample; and calculates a value of theportfolio assets for bidding purposes based on the value of each assetin said representative asset sample.
 44. A computer program according toclaim 43 further comprising computer code that segments portfolio assetsinto a predetermined number of segments based on financial attributes ofeach asset wherein said financial attributes of each asset include atleast one of an amount of unpaid principal balance (“UPB”), a collateraltype, whether the loan is secured, whether the loan is unsecured, realestate security, non-real estate security, a litigation status, aborrower operational status, and payment behavior.
 45. A computerprogram according to claim 43 further comprising computer code thatsegments portfolio assets by: assigning financial attributes to eachasset in said portfolio wherein said financial attributes include atleast one of an amount of unpaid principal balance (“UPB”), a collateraltype, whether the loan is secured, whether the loan is unsecured, realestate security, non-real estate security, a litigation status, aborrower operational status, and payment behavior; and categorizing eachasset in said portfolio based on said financial attributes assigned toeach portfolio asset.
 46. A computer program according to claim 43further comprising computer code that selects a representative sample ofassets from each segment based on a predetermined percentage of unpaidprincipal balance (“UPB”) of said portfolio assets.
 47. A computerprogram according to claim 43 further comprising computer code thatperforms an iterative and adaptive valuation in which each asset in saidrepresentative asset sample is individually valued.
 48. A computerprogram according to claim 47 further comprising computer code thatperforms an iterative and adaptive valuation by: underwriting each assetin said representative asset sample to generate underwriting data;valuing each asset in said representative asset sample based onunderwriting data; segmenting each asset in said representative assetsample based on asset characteristics such that each asset in saidrepresentative asset sample is categorized with assets having similarasset characteristics; applying a stopping criteria; and valuing saidportfolio assets for bidding purposes by comparing said assetcharacteristics of said assets in said representative asset sample tosaid portfolio assets and extrapolating the value of said portfolioassets from the value of each asset in said representative asset sample.49. A computer program according to claim 48 further comprising computercode that stores said underwriting data in a centralized database.
 50. Acomputer program according to claim 48 further comprising computer codethat underwrites each asset in said representative asset sample by:collecting financial and business information relating to each asset insaid representative asset sample; performing collateral valuations forat least one asset in said representative asset sample; and utilizingcredit bureau information for at least one asset in said representativeasset sample.
 51. A computer program according to claim 48 furthercomprising computer code that applies a stopping criteria by performingan R-Squared analysis.
 52. A computer program according to claim 48further comprising computer code that applies a stopping criteria by:valuing said representative asset sample based on said underwritingdata; generating a valuation model for valuing said portfolio assets forbidding purposes by extrapolating the value of said portfolio assetsfrom the value of said representative asset sample; utilizing saidvaluation model to re-value said representative asset sample; anddetermining whether the value of said representative asset sample basedon said underwriting data and the value of said representative assetsample based on said valuation model are substantially equal.
 53. Acomputer program according to claim 43 further comprising computer codethat calculates a value of said portfolio assets for bidding purposesby: segmenting each asset in said representative asset sample based onasset characteristics such that each asset in said representative assetsample is categorized with assets having similar asset characteristics;comparing the asset characteristics of the assets in said representativeasset sample to said portfolio assets; extrapolating the value of saidportfolio assets from the value of each asset in said representativeasset sample; and calculating a total value of said portfolio based onsaid extrapolation.
 54. A computer program according to claim 43 furthercomprising computer code that generates a valuation model for use inbidding on said asset portfolio.
 55. A computer program embodied on acomputer readable medium for performing snapshot valuation of portfolioassets, said computer program comprising computer code that: segmentsportfolio assets into a predetermined number of segments based onfinancial attributes of each asset; selects a representative sample ofassets from each segment; performs an iterative and adaptive valuationin which each asset in said representative asset sample is individuallyvalued, said iterative and adaptive valuation comprises underwritingeach asset in said representative asset sample to generate underwritingdata, valuing each asset in said representative asset sample based onunderwriting data, segmenting each asset in said representative assetsample based on asset characteristics such that each asset in saidrepresentative asset sample is categorized with assets included in saidrepresentative asset sample having similar asset characteristics, andapplying a stopping criteria; and values said portfolio assets forbidding purposes when said stopping criteria is satisfied by comparingasset characteristics of the assets in said representative asset sampleto said portfolio assets and extrapolating the value of said portfolioassets from the value of each asset in said representative asset sample.56. A computer program according to claim 55 further comprising computercode that: increases the size of the representative sample of assetswhen said stopping criteria is not satisfied; performs an iterative andadaptive valuation in which each asset in said increased representativeasset sample is individually valued, said iterative and adaptivevaluation includes underwriting each asset in said increasedrepresentative asset sample to generate underwriting data, valuing eachasset in said increased representative asset sample based onunderwriting data, segmenting each asset in said increasedrepresentative asset sample based on asset characteristics such thateach asset in said increased representative asset sample is categorizedwith assets included in said increased representative asset samplehaving similar asset characteristics, and applying said stoppingcriteria; and values said portfolio assets for bidding purposes whensaid stopping criteria is satisfied by comparing asset characteristicsof the assets in said increased representative asset sample to saidportfolio assets and extrapolating the value of said portfolio assetsfrom the value of each asset in said increased representative assetsample.